Target
Retail · Retail
- HQ
- Minneapolis, US
- Founded
- 1962
- Size
- 400,000+
- Website
- target.com
Target currently has 28 active job listings related to artificial intelligence. The majority of these roles, 61%, are focused on agents, with data roles making up another 14%. Engineering is the primary function hiring for these positions, with the United States and India each accounting for 14 roles. Frequent technology tags include model serving, agent orchestration, and RAG, suggesting a focus on deploying and managing AI models. Over the last 30 days, Target has posted 20 new AI roles, representing an 82% increase compared to the previous 30-day period.
Currently tracking 25 active AI roles, down 87% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $75k–$356k (avg $183k).
Target currently has 38 active AI-related roles in our index. The most common open titles are: Lead Operations Research Scientist (3), Sr Engineer - Target India (3), Director Product Management - Physical Intelligence, Director of Engineering - AI Security, Lead Data Scientist- AML. Most positions are in Engineering and Product.
Target's active AI hiring is concentrated in: agents (71%), serving infrastructure (11%), data (11%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Target is hiring AI talent in: United States (19 roles), India (19 roles).
Job postings at Target most frequently reference: agent orchestration, model serving, llm observability, rag, inference infra.
In the past 30 days, Target has posted 24 new AI-related roles. That is a +50% change versus the prior 30 days (16 → 24).
Retail · Retail
| Title | Stage | AI score |
|---|---|---|
| Director Product Management - Physical Intelligence Director of Product Management for Physical Intelligence at Target, focusing on turning physical environment signals (computer vision, RFID, smart building) into reusable intelligence capabilities. The role involves setting strategic vision, managing a team of product owners, driving product discovery, and leveraging data and analytics to deliver innovative solutions. Requires deep understanding of AI/ML concepts and experience building enterprise capabilities. | Agent | 7 |